k
4442e97f28
New backend pipeline: 8 free public macro signals fetched in parallel,
upserted once per calendar day, served via /api/macro/{snapshot,history}.
- AHR999 (computed from Binance 200d klines)
- Altcoin Season Index (CoinGecko top-50 30d)
- Fear & Greed (alternative.me)
- BTC dominance, ETH/BTC ratio
- Stablecoin supply (DeFiLlama)
- Spot BTC ETF net flow (Farside)
- BTC perp open interest (Binance fapi)
Each fetcher is independently @_none_on_fail decorated so one outage
can't take down the snapshot; scoring renormalises across whichever
indicators returned a value. Daily cron at 03:00 UTC; on startup a
fire-and-forget bootstrap fills today's row if missing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
336 lines
14 KiB
Python
336 lines
14 KiB
Python
"""Individual fetchers for each macro indicator.
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Each function is an async coroutine that returns a dict shaped like:
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{ "value": float | int | None,
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"label": Optional[str], # only some indicators
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"raw": <upstream payload> } # for debugging / re-scoring
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Every fetcher MUST tolerate upstream failure — return {"value": None} rather
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than raise — so one dead API can't take down the whole snapshot.
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Public, free, no-key sources only:
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AHR999 : derived from BTC daily closes (Binance fapi)
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Altcoin Season Index : CoinGecko top-50 90-day relative performance
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Fear & Greed : api.alternative.me/fng (no auth)
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BTC Dominance : CoinGecko /global
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ETH/BTC Ratio : Binance kline ETHBTC daily
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Stablecoin Supply : DeFiLlama /stablecoins
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ETF Net Flow (1d) : Farside Investors HTML scrape
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BTC Open Interest : Binance fapi /futures/data/openInterestHist
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"""
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from __future__ import annotations
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import logging
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import math
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import re
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from datetime import datetime, timedelta, timezone
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from typing import Any, Optional
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import httpx
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logger = logging.getLogger(__name__)
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# A vanilla User-Agent. CoinGecko + alternative.me + DeFiLlama all happily
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# serve "Mozilla/5.0"; some get suspicious of anything that looks bot-like
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# (e.g. python-httpx default UA returns 400 on /global).
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UA = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 14_0) AppleWebKit/605.1.15"}
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DEFAULT_TIMEOUT = 20
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def _none_on_fail(name: str):
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"""Decorator: log+swallow exceptions from a fetcher and return {value: None}."""
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def deco(fn):
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async def wrapper(*a, **kw):
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try:
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return await fn(*a, **kw)
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except Exception as exc:
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logger.warning("macro fetch %s failed: %s (%s)",
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name, type(exc).__name__, exc)
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return {"value": None, "raw": {"error": f"{type(exc).__name__}: {exc}"}}
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return wrapper
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return deco
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def _utc_midnight_ms(now: Optional[datetime] = None) -> int:
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dt = now or datetime.now(timezone.utc)
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midnight = dt.replace(hour=0, minute=0, second=0, microsecond=0)
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return int(midnight.timestamp() * 1000)
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def _drop_in_progress_daily_klines(rows: list[list], now: Optional[datetime] = None) -> list[list]:
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"""Binance daily klines are keyed by OPEN time. If the latest row opened at
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today's 00:00 UTC, that candle is still in progress and should not be used
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for daily snapshots."""
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if not rows:
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return rows
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cutoff = _utc_midnight_ms(now)
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return [row for row in rows if int(row[0]) < cutoff]
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def _latest_closed_daily_point(rows: list[dict], now: Optional[datetime] = None) -> Optional[dict]:
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"""Same idea as `_drop_in_progress_daily_klines`, but for daily point
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series keyed by `timestamp`."""
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if not rows:
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return None
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cutoff = _utc_midnight_ms(now)
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closed = [row for row in rows if int(row.get("timestamp", 0)) < cutoff]
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return closed[-1] if closed else None
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def _parse_farside_latest_total(html: str) -> dict:
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"""Extract the most recent dated row from Farside's historical table.
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The all-data table is chronological from oldest to newest, so the first
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date row is NOT the latest one.
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"""
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m = re.search(r"<tbody[^>]*>(.*?)</tbody>", html, re.DOTALL | re.IGNORECASE)
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if not m:
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return {"value": None, "raw": {"error": "tbody not found"}}
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body = m.group(1)
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rows = re.findall(r"<tr[^>]*>(.*?)</tr>", body, re.DOTALL | re.IGNORECASE)
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latest: Optional[dict] = None
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for row in rows:
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cells = re.findall(r"<td[^>]*>(.*?)</td>", row, re.DOTALL | re.IGNORECASE)
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if not cells:
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continue
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date_text = re.sub(r"<[^>]+>", "", cells[0]).strip()
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if not re.match(r"\d{1,2}\s+[A-Za-z]+\s+\d{4}", date_text):
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continue
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last_text = re.sub(r"<[^>]+>", "", cells[-1]).strip()
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num = last_text.replace(",", "").replace("(", "-").replace(")", "")
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try:
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millions = float(num)
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row_date = datetime.strptime(date_text, "%d %b %Y").date()
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except ValueError:
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continue
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candidate = {
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"value": round(millions * 1_000_000, 2),
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"raw": {"date": date_text, "millions_usd": millions},
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"_date": row_date,
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}
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if latest is None or candidate["_date"] > latest["_date"]:
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latest = candidate
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if latest is None:
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return {"value": None, "raw": {"error": "no parseable rows"}}
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latest.pop("_date", None)
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return latest
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# ── 1. AHR999 ───────────────────────────────────────────────────────────────
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# Formula: AHR999 = (price / 200d MA) × (price / age_fit_price)
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# age_fit_price = 10 ** (5.84 * log10(days_since_2009_01_03) - 17.01)
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# Below 0.45 historically marks accumulation zones; above 1.2 marks
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# "expensive" regime that invalidates a bottom thesis.
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_AHR999_GENESIS = datetime(2009, 1, 3, tzinfo=timezone.utc)
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@_none_on_fail("ahr999")
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async def fetch_ahr999() -> dict:
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"""Compute AHR999 from the last 200 daily BTC closes (Binance fapi)."""
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end_ms = int(datetime.now(timezone.utc).timestamp() * 1000)
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start_ms = end_ms - 260 * 24 * 3600 * 1000 # extra buffer after dropping in-progress day
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as c:
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r = await c.get(
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"https://fapi.binance.com/fapi/v1/klines",
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params={"symbol": "BTCUSDT", "interval": "1d",
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"startTime": start_ms, "endTime": end_ms, "limit": 300},
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)
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r.raise_for_status()
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rows = _drop_in_progress_daily_klines(r.json())
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closes = [float(row[4]) for row in rows]
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if len(closes) < 200:
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return {"value": None, "raw": {"error": "insufficient candles", "have": len(closes)}}
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price = closes[-1]
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ma200 = sum(closes[-200:]) / 200
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days = (datetime.now(timezone.utc) - _AHR999_GENESIS).total_seconds() / 86400
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age_fit = 10 ** (5.84 * math.log10(days) - 17.01)
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ahr = (price / ma200) * (price / age_fit)
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return {
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"value": round(ahr, 4),
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"raw": {"price": price, "ma200": round(ma200, 2),
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"age_fit": round(age_fit, 2), "days": round(days, 1)},
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}
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# ── 2. Altcoin Season Index (blockchaincenter.net formula) ───────────────────
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# Take top-50 coins by market cap (excluding stablecoins + wrapped). Count how
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# many beat BTC's 90-day return. Result is the count, projected to 0-100.
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# 75+ = altseason, <25 = bitcoin season, middle = neutral.
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_STABLE_OR_WRAPPED = {
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"USDT", "USDC", "DAI", "BUSD", "TUSD", "USDD", "FDUSD", "PYUSD", "USDE",
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"WBTC", "WETH", "STETH", "WSTETH", "WEETH", "RETH",
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}
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@_none_on_fail("altcoin_season_index")
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async def fetch_altcoin_season_index() -> dict:
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"""Compute the Altcoin Season Index from CoinGecko /coins/markets.
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Original blockchaincenter.net formula uses a 90-day window, but
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CoinGecko's /coins/markets `price_change_percentage` parameter only
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accepts 1h/24h/7d/14d/30d/200d/1y — 90d returns HTTP 400. We use 30d
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as the closest practical proxy. Long-horizon altseason (which 90d
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captures better) would need per-coin /market_chart calls — 50× the
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API budget for a marginal definition improvement.
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"""
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT, headers=UA) as c:
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r = await c.get(
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"https://api.coingecko.com/api/v3/coins/markets",
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params={"vs_currency": "usd", "order": "market_cap_desc",
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"per_page": 60, "page": 1,
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"price_change_percentage": "30d"},
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)
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r.raise_for_status()
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rows = r.json()
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# Drop stablecoins + wrapped, keep top 50 of the remainder.
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eligible = [
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row for row in rows
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if (row.get("symbol") or "").upper() not in _STABLE_OR_WRAPPED
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and row.get("price_change_percentage_30d_in_currency") is not None
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][:50]
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if len(eligible) < 30:
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return {"value": None, "raw": {"error": "insufficient eligible coins",
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"have": len(eligible)}}
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btc_row = next((x for x in rows if x.get("symbol", "").upper() == "BTC"), None)
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btc_30d = btc_row.get("price_change_percentage_30d_in_currency") if btc_row else None
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if btc_30d is None:
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return {"value": None, "raw": {"error": "BTC 30d return missing"}}
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n_outperform = sum(
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1 for row in eligible
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if (row["price_change_percentage_30d_in_currency"] or -999) > btc_30d
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)
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# Project the count over `len(eligible)` to a 0–100 scale.
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index = (n_outperform / len(eligible)) * 100
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return {
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"value": round(index, 1),
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"raw": {"n_outperform": n_outperform, "of": len(eligible),
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"btc_30d_pct": round(btc_30d, 2), "window": "30d"},
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}
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# ── 3. Fear & Greed (alternative.me) ────────────────────────────────────────
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@_none_on_fail("fear_greed")
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async def fetch_fear_greed() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT, headers=UA) as c:
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r = await c.get("https://api.alternative.me/fng/?limit=1")
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r.raise_for_status()
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data = r.json()
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item = (data.get("data") or [None])[0]
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if not item:
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return {"value": None, "raw": data}
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return {
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"value": int(item.get("value", 0)),
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"label": item.get("value_classification"),
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"raw": item,
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}
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# ── 4. BTC Dominance (CoinGecko /global) ────────────────────────────────────
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@_none_on_fail("btc_dominance")
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async def fetch_btc_dominance() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT, headers=UA) as c:
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r = await c.get("https://api.coingecko.com/api/v3/global")
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r.raise_for_status()
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data = r.json()
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pct = (data.get("data", {}).get("market_cap_percentage", {}) or {}).get("btc")
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if pct is None:
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return {"value": None, "raw": data}
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return {"value": round(float(pct), 2),
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"raw": {"total_mcap_usd": data["data"]["total_market_cap"].get("usd")}}
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# ── 5. ETH/BTC Ratio (Binance ETHBTC daily) ──────────────────────────────────
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@_none_on_fail("eth_btc_ratio")
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async def fetch_eth_btc_ratio() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as c:
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r = await c.get(
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"https://fapi.binance.com/fapi/v1/klines",
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params={"symbol": "ETHBTC", "interval": "1d", "limit": 3},
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)
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# fapi may 404 ETHBTC; fall back to spot kline endpoint via data-api host.
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if r.status_code == 400 or r.status_code == 404:
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r = await c.get(
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"https://data-api.binance.vision/api/v3/klines",
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params={"symbol": "ETHBTC", "interval": "1d", "limit": 3},
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)
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r.raise_for_status()
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rows = _drop_in_progress_daily_klines(r.json())
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if not rows:
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return {"value": None, "raw": rows}
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close = float(rows[-1][4])
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return {"value": round(close, 6), "raw": {"close": close, "n_rows": len(rows)}}
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# ── 6. Stablecoin Total Supply (DeFiLlama) ───────────────────────────────────
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@_none_on_fail("stablecoin_supply")
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async def fetch_stablecoin_supply() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT, headers=UA) as c:
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r = await c.get(
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"https://stablecoins.llama.fi/stablecoins",
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params={"includePrices": "true"},
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)
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r.raise_for_status()
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data = r.json()
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# Sum circulating peggedUSD across all stables.
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total = 0.0
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for stable in data.get("peggedAssets", []):
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circ = stable.get("circulating", {}).get("peggedUSD")
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if isinstance(circ, (int, float)):
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total += float(circ)
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if total <= 0:
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return {"value": None, "raw": {"error": "no peggedUSD totals found"}}
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return {"value": round(total, 2),
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"raw": {"n_stables": len(data.get("peggedAssets", []))}}
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# ── 7. BTC Spot ETF Net Flow 1d (Farside) ────────────────────────────────────
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# Farside doesn't have a JSON API but their daily flow page is parseable. We
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# pull the most recent row from the All ETFs sum.
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@_none_on_fail("etf_flow")
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async def fetch_etf_flow() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT, headers=UA,
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follow_redirects=True) as c:
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r = await c.get("https://farside.co.uk/bitcoin-etf-flow-all-data/")
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r.raise_for_status()
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return _parse_farside_latest_total(r.text)
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# ── 8. BTC Open Interest (Binance fapi) ──────────────────────────────────────
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@_none_on_fail("btc_open_interest")
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async def fetch_btc_open_interest() -> dict:
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as c:
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r = await c.get(
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"https://fapi.binance.com/futures/data/openInterestHist",
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params={"symbol": "BTCUSDT", "period": "1d", "limit": 4},
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)
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r.raise_for_status()
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rows = r.json()
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latest = _latest_closed_daily_point(rows)
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if not latest:
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return {"value": None, "raw": rows}
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notional = float(latest.get("sumOpenInterestValue", 0))
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return {"value": round(notional, 2),
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"raw": {"contracts": float(latest.get("sumOpenInterest", 0)),
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"timestamp": latest.get("timestamp")}}
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